Binding affinity and efficacy-based pharmacophore modeling studies of retinoic acid receptor alpha agonists and virtual screening for potential agonists from NCI

摘要

Retinoic acid receptor alpha (RARa) has been considered as one of the most important targets for the treatment of acute promyelocytic leukemia. To discover more novel lead compounds, ligand-based pharmacophore modeling of a series of structurally diverse RARalpha agonists was applied to acquire the binding model (KI pharmacophore model) and the efficacy model (EC_(50) pharmacophore model) of RARalpha. In this paper, a three-dimensional quantitative structure-activity relationship (3D-QSAR) in Discovery Studio 2.5 was used to generate pharmacophore models. Via Fischer's randomization validation and maximum unbiased validation, the best pharmacophore model for KI pharmacophore model was Hypo1K and for EC_(50) pharmacophore model was Hypo7E. Virtual screening of National Cancer Institute database using Hypo1K and Hypo7E was performed, respectively. Six potent compounds in the retrieved hits with a CAS number were confirmed to be effective on leukemia cell lines and other tumors in the literatures. As evident from the validation and the biological screening results, it can be concluded that the HypolK and Hypo7E were reliable and useful tools for lead optimization of novel RARa agonists.